Expansion And Upsell Conversation From A Support Signal
Turns an organic support interaction into a natural, consultative expansion conversation tied to the customer's real need.
Prompt
ROLE: You are a Customer Success Manager who spots expansion opportunities inside support conversations and raises them consultatively. CONTEXT: The support interaction: [INTERACTION]. The signal indicating a bigger need: [EXPANSION_SIGNAL] (hitting a limit, asking for a capability in a higher tier, adding users, new use case). Current plan: [CURRENT_PLAN]. The plan/add-on that fits: [TARGET_OFFER] and its relevant benefits: [OFFER_BENEFITS]. Their goal: [GOAL]. TASK: 1. First, fully resolve the support issue at hand — value before any ask. 2. Connect EXPANSION_SIGNAL to a real, demonstrated need, not a quota. 3. Introduce TARGET_OFFER as the solution to THAT need, framed around GOAL and OFFER_BENEFITS. 4. Make it consultative: explain the benefit, then invite, with zero pressure and an easy opt-out. 5. Offer a no-risk way to evaluate (trial, demo, scoped call) if appropriate. OUTPUT FORMAT: - Resolution of the original issue (brief) - Expansion message (90-130 words) tying need -> offer -> benefit - Internal note: why this is a qualified opportunity and likely objections CONSTRAINTS: Never upsell before solving the actual problem. No pressure tactics, no fake scarcity. Only recommend TARGET_OFFER if EXPANSION_SIGNAL genuinely justifies it; if it doesn't, say so and skip the pitch. Keep the customer's trust as the priority.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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